A user may query a Geographic Information System (GIS) for determining spatial relations between geographical locations. The spatial relations may be associated to directions, proximity or containment between the geographical locations. In response to a search query input by the user, the GIS may guide the user. In one example, the user may query the GIS for determining a direction to a specific geographical location/orientation/direction such as “hotels towards north direction.” The directions are broadly categorized into east, west, north, and south direction. Based upon the user query, the GIS may determine a location of the user and may subsequently determine hotels present towards the north of the user.
In one instance, the search query presented by the user to the GIS may relate to containment within a geographical location. For example, the search query may be “hotels within Delhi.” The search results may not involve any fuzziness as geographical coordinates of Delhi are precisely defined. The GIS may thus determine the hotels present within the geographical coordinates bounding an area of Delhi, and may subsequently present the search results to the user.
However, in another instance, the search query presented by the user may be related to proximity/nearness. For example, the search query may be “hotels nearby Delhi.” In the present case, the search query involves a keyword “nearby.” A perception of the word “nearby (near)” may vary with each user as scope of the word is not defined/crisp. Thus, every time the GIS presents the search results to the user, there may be fuzziness associated with the search results due to undefined terms used in the search query.
In order to receive appropriate search results related to queries having undefined/subjective/relative terms like near, a user's proximity model may be created. The user's proximity model may determine a perception of the user with respect to the queries comprising such words/terms. Conventional GIS may accept a binary feedback for creating the user's proximity model and may not be able to create an appropriate user's proximity model based upon the binary feedback.
Further, the conventional GIS, while creating the user's proximity model, may present only a single point to the user for accepting the user feedback. Therefore, conventional GIS may require a large number of iterations to create the user's proximity model and thus increase complexity.